Ah yes, December 2025...such a long, long time ago...

>Actually he provides sources when he analyses stuff and imho much better than the usual corporate

You said it was likely an internal leak to the WSJ "according to Ed Zitron". Did Ed have a source for that, or was it just vibes?

[dead]

Depreciation is part of the cost of inference. Inference happens in GPUs that have a relatively short lifespan.

Those GPUs are very expensive.

Inference is expensive because a GPU can only process a certain amount of requests in a given timeframe. Remember that Anthropic is constrained in compute.

If they are constrained, it means that those GPUs are not idle. If they have more customers, they will need more GPUs.

If they have to play silly games using EBITDA to be "profitable", then it means that they need to ramp up prices a lot more than they already did.

Which is why in these discussions I always say that inference is also extremely expensive. Too many people like to pretend without any evidence that inference is cheap.

> "in 6 months" that AI will be doing all of SWE work

I assume this is the quote you're referring to from Davos?

"I have engineers within Anthropic who say I don’t write any code anymore. I just let the model write the code, I edit it. I do the things around it… we might be six to twelve months away from when the model is doing most, maybe all of what SWEs do end to end."

that was in Jan, he said "might" and he said 6-12 months. Yes! Let's hold him accountable for saying reasonable things!

I work in big tech and probably 90% of code over the last month has been written by AI. And I suspect it's probably higher within Anthropic, which is probably what he's basing his opinion on.

So, he's closer to correct than not.

That said, your recollection is also flawed. It was in mid-March, and here's the relevant quotes:

>I think we’ll be there in three to six months—where AI is writing 90 percent of the code. And then in twelve months, we may be in a world where AI is writing essentially all of the code.

[...]

>But the programmer still needs to specify, you know, what are—what are the conditions of what you’re doing, what—you know, what is the overall app you’re trying to make, what’s the overall design decision? How do we collaborate with other code that’s been written? You know, how do we have some common sense on whether this is a secure design or an insecure design?

[...]

>So as long as there are these small pieces that a programmer, a human programmer, needs to do, the AI isn’t good at, I think human productivity will actually be enhanced. But on the other hand, I think that eventually all those little islands will get picked off by AI systems.

With another 3-4 months left on the clock, his prediction seems remarkably on point for at least certain organizations and domains.

I welcome you to also hold yourself accountable in the coming months if this trend continues. ;)

Elon playbook

Yes, when he made that claim back in 2024 they were spending like $100M to train a model.

In the meanwhile, Google AI search still says the next year after 2026 will be 2028.